Skin color segmentation using coarse-to-fine region on normalized RGB chromaticity diagram for face detection

This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. I-ace skill is extracted from color images using it coarse skin region with fixed boundaries followed by a fine skill region with variable boundaries. Two newly developed histograms that...

Full description

Bibliographic Details
Main Authors: Soetedjo, Aryuanto, Yamada, Koichi
Format: Article
Language:English
Published: The Institute of Electronics, Information and Communication Engineers 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/2174/
http://shdl.mmu.edu.my/2174/1/Skin%20color%20segmentation%20using%20coarse-to-fine%20region%20on%20normalized%20RGB%20chromaticity%20diagram%20for%20face%20detection.pdf
Description
Summary:This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. I-ace skill is extracted from color images using it coarse skin region with fixed boundaries followed by a fine skill region with variable boundaries. Two newly developed histograms that have prominent peaks of skill color and non-skill colors are employed to adjust the boundaries of the skin region The proposed approach does not need a skin color model. which depends on it specific camera parameter and is usually limited to a particular environment condition. and no sample images are required. The experimental results using color face images of Various races under varying lighting conditions and complex backgrounds, obtained front four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11], [12] .